Difference between revisions of "2015 Summer Project Week:BigDataFeatures"
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* Matthew Toews, École de Technologie Supérieure | * Matthew Toews, École de Technologie Supérieure | ||
* William Wells, BWH, Harvard Medical School | * William Wells, BWH, Harvard Medical School | ||
| + | * Raul San Jose Estepar, BWH, Harvard Medical School | ||
* Tina Kapur, BWH, Harvard Medical School | * Tina Kapur, BWH, Harvard Medical School | ||
| + | * Utsav Pardasani, Robarts (Observing!) | ||
| + | * Salvatore Scaramuzzino (Interested!) | ||
| + | * Andrey Fedorov, BWH | ||
| + | ==3D SIFT-Rank Visualization, SLC 2015, IPMI 2015 == | ||
| + | [[File:Lung-ct.png|300px|thumb|left|Lung CT Features]] | ||
| + | [[File:Img-feat.png|300px|thumb|left|Data Reduction for 20000 lung CT volumes]] | ||
| + | [[File:3D_SIFT_Prostate.png|300px|thumb|left|Prostate US Features]] | ||
==Project Description== | ==Project Description== | ||
| Line 18: | Line 26: | ||
* Application domains: registration, segmentation, classification. | * Application domains: registration, segmentation, classification. | ||
* Image domains: lung CT, brain MR, prostate and brain ultrasound. | * Image domains: lung CT, brain MR, prostate and brain ultrasound. | ||
| − | * Clinical | + | * Clinical use case scenarios: chronic obstructive pulmonary disease, Alzheimer's disease, cancer. |
</div> | </div> | ||
<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
<h3>Approach, Plan</h3> | <h3>Approach, Plan</h3> | ||
* Discussion and documentation | * Discussion and documentation | ||
| − | + | * Algorithms: fast KNN methods, hashing, robust estimation (RANSAC, Hough transform). | |
| − | + | * Mathematical formalisms: probabilistic inference, kernel methods, manifold learning. | |
</div> | </div> | ||
<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
<h3>Progress</h3> | <h3>Progress</h3> | ||
| − | * | + | 1) Discussed applications of 3D SIFT-Rank |
| + | * Analyzing COPD - lung CT - Raul San Jose Estepar | ||
| + | * Identifying similar cases - general MR/CT/US - Tobias Penzkofer | ||
| + | * Infant brain analysis - brain MR - Steve Pieper | ||
| + | * Prostate segmentation - MR/US - Andrey Federov, Salvatore Scaramuzzino | ||
| + | * Astronomical galaxy classification - radio data cube (lambda=21cm) - Davide Punzo | ||
| + | 2) Coding for kernel regression framework (C++) | ||
</div> | </div> | ||
</div> | </div> | ||
==References== | ==References== | ||
| + | [http://www.na-mic.org/Wiki/index.php/3D_SIFT_VIEW] SIFT View, NAMIC 2015 SLC Project Week <br> | ||
| + | [http://www.matthewtoews.com/publications.html] "A Feature-based Approach to Big Data Analysis of Medical Images", M. Toews, C. Wachinger, R. S. J. Estepar, W.M. Wells III. | ||
| + | Information Processing in Medical Imaging (IPMI), 2015.<br> | ||
| + | [http://www.matthewtoews.com/publications.html] "Keypoint Transfer Segmentation", C. Wachinger, M. Toews, G. Langs, W.M. Wells IIIi, P. Golland. Information Processing in Medical Imaging (IPMI), 2015. | ||
Latest revision as of 15:17, 24 June 2015
Home < 2015 Summer Project Week:BigDataFeatures
Key Investigators
- Matthew Toews, École de Technologie Supérieure
- William Wells, BWH, Harvard Medical School
- Raul San Jose Estepar, BWH, Harvard Medical School
- Tina Kapur, BWH, Harvard Medical School
- Utsav Pardasani, Robarts (Observing!)
- Salvatore Scaramuzzino (Interested!)
- Andrey Fedorov, BWH
3D SIFT-Rank Visualization, SLC 2015, IPMI 2015
Project Description
Objective
- This project will investigate the use of 3D SIFT-RANK image features for organizing and deriving information from 3D medical image volumes.
- Technology: invariant feature extraction, descriptor representation.
- Application domains: registration, segmentation, classification.
- Image domains: lung CT, brain MR, prostate and brain ultrasound.
- Clinical use case scenarios: chronic obstructive pulmonary disease, Alzheimer's disease, cancer.
Approach, Plan
- Discussion and documentation
- Algorithms: fast KNN methods, hashing, robust estimation (RANSAC, Hough transform).
- Mathematical formalisms: probabilistic inference, kernel methods, manifold learning.
Progress
1) Discussed applications of 3D SIFT-Rank
- Analyzing COPD - lung CT - Raul San Jose Estepar
- Identifying similar cases - general MR/CT/US - Tobias Penzkofer
- Infant brain analysis - brain MR - Steve Pieper
- Prostate segmentation - MR/US - Andrey Federov, Salvatore Scaramuzzino
- Astronomical galaxy classification - radio data cube (lambda=21cm) - Davide Punzo
2) Coding for kernel regression framework (C++)
References
[1] SIFT View, NAMIC 2015 SLC Project Week
[2] "A Feature-based Approach to Big Data Analysis of Medical Images", M. Toews, C. Wachinger, R. S. J. Estepar, W.M. Wells III.
Information Processing in Medical Imaging (IPMI), 2015.
[3] "Keypoint Transfer Segmentation", C. Wachinger, M. Toews, G. Langs, W.M. Wells IIIi, P. Golland. Information Processing in Medical Imaging (IPMI), 2015.
